Many different conditions and parameters contribute to the overall quality of a resulting weld. Consequently, manufacturers of electric arc welders have attempted to monitor operation of the welder to determine the quality of the weld and the efficiency of the welder during operation in a manufacturing facility. One attempt to monitor an electric arc welder is illustrated in U.S. Pat. No. 6,051,805 to Vaidya (hereinafter “Vaidya”) where a computer or other programmed instrument is employed to monitor average current and the efficiency of the welding operation, which efficiency is expressed as a ratio of the time welding is performed to the total time of the work shift. In accordance with standard technology, this disclosed monitoring system includes a first control circuit which is in the form of a central processing unit with standard accessories such as RAM and EPROM. A second control circuit is connected to the first circuit to input and output information during the monitoring procedure. The monitor gathers information over a period of time which is disclosed as extending over a few hours or up to 999 hours. The monitor determines welding efficiency and monitors time to determine average current and accumulated arc welding time for overall efficiency.
Vaidya discloses a capability of monitoring the current and wire feed speed, as well as gas flow during the welding procedure. All of this information is stored in appropriate memory devices for subsequent retrieval of the operating characteristics of the welder during the welding process. In this way, the productivity of the welder can be measured to calculate cost efficiency and other parameters. Monitoring of the electric arc welder, as suggested in Vaidya, has been attempted by other manufacturers to measure average current during a welding process. However, measuring average current, voltage, wire feed speed or other parameters during a welding process and using this data for recording the performance of the welding operation has not been satisfactory. In the past, monitoring devices have had no pre-knowledge of the parameters being monitored.
Consequently, monitoring of parameters such as current, voltage and even wire feed speed in the past, even using the technology set forth in Vaidya, has been chaotic in response and incapable of determining the actual stability of the electric arc or whether the welding process is above or below desired parameter values. This information must be known for the purpose of rejecting a welding cycle and/or determining the quality of the weld performed during the welding cycle with desired accuracy. In summary, monitoring the operation of an electric arc welder when used for a variety of welding processes has not been satisfactory because there is no prior knowledge which can be used for the purposes of evaluating the welding process during its implementation.
Overcoming these drawbacks, U.S. Pat. No. 6,441,342 to Hsu (hereinafter “Hsu”) discloses a monitor and method of monitoring an electric arc welder as the welder performs a selected arc welding process that creates information on the operation of the welder. Accordingly, use of standard, high power computer technology can be used on equally precise and intelligent data generated by the monitor. The monitor and monitoring system of Hsu employs known information during the welding process. The information is fixed and not varying. The monitor concentrates on specific aspects of the welding process to employ prior knowledge which is compared to actual performance. Thus, the stability and acceptable magnitudes or levels of a selected parameter is determined during a specific aspect of the welding process. The weld process is separated into fixed time segments with known desired parameters before monitoring. Then this data can be processed by known computer techniques to evaluate aspects of the weld cycles.
Hsu discloses that the welding process is carried out by an electric arc welder generating a series of rapidly repeating wave shapes. Each wave shape constitutes a weld cycle with a cycle time. Each weld cycle (i.e., wave shape) is created by a known wave shape generator used to control the operation of the welder. These wave shapes are divided into states, such as in a pulse welding process, a state of background current, ramp up, peak current, ramp down, and then back to background current. By dividing the known driving wave shape into states defined as time segments of the generated arc characteristics, any selected one of the states can be monitored. Indeed, many states can be multiplexed. For instance, in the pulse welding process the state related to the peak current can be monitored. Hsu discloses that the state of the welding process is monitored by being read at a high rate preferably exceeding 1.0 kHz. Each of the actual welding parameters, such as current, voltage or even wire feed speed is detected many times during each peak current state of the wave shape used in the pulse welding process. In this manner, the ramp up, ramp down, and background current are ignored during the monitoring process of the peak current state.
Consequently, the peak current is compared with a known peak current. A function of the peak current can be used to detect variations in the actual peak current output from the electric arc welder. In Hsu, a minimum level and a maximum level on the lower and higher side of the command peak current are used to determine the level of the peak current many times during each peak current state of the pulse weld wave shape. Whenever the current exceeds the maximum, or is less than the minimum, this event is counted during each wave shape. The total deviations or events are counted for a weld time (i.e., a time during which a welding process or some significant portion thereof is carried out). If this count is beyond a set number per wave shape or during the weld time, a warning may be given that this particular welding process experienced unwanted weld conditions. Indeed, if the count exceeds a maximum level the weld is rejected. This same capability is used with a statistical standard deviation program to read the peak current many times during each peak current state of the wave shape to sense the magnitude of the standard deviation. In practice, the standard deviation is the root-mean-square (RMS) deviation calculation by the computer program. In Hsu, the average peak current is calculated and recorded as well as the level conditions and the stability characteristics. The RMS of the current or voltage is also determined for each of the states being monitored, for example, the peak current state of a pulse wave shape. While the peak current level or standard elevation is monitored, the background current stage can be monitored by current level and duration.
Hsu discloses selecting a state in the wave shape and comparing the desired and known command signals for that state to the actual parameters of the welding process during that monitored state. The selection is based on prior knowledge of the waveform generator. For example, at a specific wire feed speed WFS1, the waveform generator is programmed to adjust peak current to control arc length. The “informed” monitor then selects the peak current segment as the monitored state, when welding at this wire feed speed WFS1. At another wire feed speed WFS2, however, the waveform generator is programmed to adjust background time to control arc length (and not peak current). The “informed” monitor then selects the background time as the monitored state and parameter, when welding at this wire feed speed WFS2. In contrast, a posteriori monitor has no idea that at different wire feed speeds, different aspects of the waveform should be monitored to detect arc stability. Monitoring background time at wire feed speed WFS1 or monitoring peak current at wire feed speed WFS2, in this example, would be very ineffective. Thus, Hsu discloses using a time segment of the wave shape for monitoring this segment of the wave shape using prior knowledge of the desired values. This allows actual monitoring of the electric arc welding process and not merely an averaging over the total wave shape.
In Hsu, the monitor is characterized by the use of prior knowledge, as opposed to the normal process of merely reading the output parameters experienced during the welding process. Consequently, the monitoring greatly simplifies the task of detecting normal behavior of a welder when the normal behavior is a function of time and differs during only one aspect of the welding process. The teachings of Hsu are not as applicable to monitoring voltage in a constant voltage process, because the desired level of voltage is a known characteristic during the total weld cycle. However, in other welding processes when both the voltage and current vary during different segments of the wave shape, the method of Hsu gives accurate readings of stability, RMS, standard deviation, average, below minimum and above maximum before the actual parameter being monitored during selected segments of the wave shape.
According to Hsu, the time varying welding processes, such as pulse welding and short circuit welding, are monitored with precise accuracy and not by reading general output information. The monitor is activated at a selected time in each wave form which is the selected state or segment of the wave shape. The monitor compares actual parameters to the desired parameters in the form of command signals directed to a power supply of the welder. In Hsu, monitoring can occur during only specific segments of the wave shape; however, in exceptional events, such as when the arc is extinguished or when there is a short circuit, a computerized subroutine is implemented by either voltage sensing or current sensing to restart the arc and/or correct the short. The subroutines for these events run parallel to the monitoring program. Consequently, these exceptions do not affect the overall operation of the monitor. These subroutines are constructed as exceptional states or time segments. The parameters or signals within these exceptional states are monitored in a similar fashion as described above.
In Hsu, production information over a calendar time, shift or even by operator can be accumulated for the purposes of evaluating the operation or efficiency of a welder. The monitoring of each weld cycle by monitoring a specific segment or state of the wave shape allows accumulation of undesired events experienced over time. This also allows a trend analysis so that the operator can take corrective actions before the welding process actually produces defective production welds. Trend analysis, defect analysis, accumulated defects, logging of all of these items and related real time monitoring of the electric arc welder allows direct intervention in a timely manner to take preventive actions as opposed to corrective actions.